The present invention concerns a pixel density converter which converts the density of pixels in image data formed by a computer reading with an image sensor. In particular, it relates to a pixel density converter whereby the intensity level of each pixel, based on image data expressed in multi-valued notation, is expressed in binary notation, while the number of pixels is reduced.
In the case of a facsimile machine, for example, when the size of the print-out paper at the receiving end is smaller than the image record at the transmitting end, the image data are reduced before transmission. Or, when certain image information undergoes image editing whereby it is inserted into a prescribed image area, this image information undergoes appropriate reduction. Similarly, photocopiers which copy image information read by an image sensor at a specified rate of magnification often employ image data reduction.
FIG. 13 shows an example of one conventional principle of pixel density conversion. The example shown in FIG. 13 illustrates a case of a linear reduction to 25 percent. In this case, of the pixel series A,B,C, etc. shown in part (a) of the diagram, one in every four pixels is extracted and the remaining ones discarded, forming the pixel row shown in part (b) of the diagram. In this example, pixels A,E,I, etc. are extracted, while pixels B,C,D,F,G, etc. are discarded. When the respective intensity levels of the extracted pixels A,E,I, etc. are expressed in multi-valued notation, these are then converted to binary notation using a fixed threshold value, and binary encoded image data are produced, as shown in part (c) of the diagram.
FIG. 14 shows an example of another conventionally used principle of pixel density conversion. This example similarly shows a case of reduction to 25 percent. The pixel series A,B,C, etc., shown in part (a) of FIG. 14 is converted to binary notation, and binary encoded image data are produced, as shown for example in part (b). These image data are in turn assembled in groups of four pixels each and a logic total is taken for each group. In this way, binary encoded image data are produced following reduction, as shown in part (c) of the diagram.
While the process of a pixel density converter using the principle shown in FIG. 13 is straightforward since it involves a simple thinning-out of the image data, there have been problems of considerable deterioration of image information due to pixel disappearance. For example, in this case there has been the possibility that lines and points with a breadth of less than 4 pixels could be lost.
In contrast, with a pixel density converter using the principle shown in FIG. 14, a logic total of the image data is taken in order to prevent disappearance of the image information. Nevertheless, since the logic total is taken after conversion from multi-valued to binary notation, the condition of the original image data is insufficiently preserved and image degradation, etc., occurs; thus, no effective improvement has been achieved against deterioration of image information.
In addition, another problem with conventional pixel density converters has been that image processing has required a considerable amount of time, since it has been normal for logic processes, such as totaling, to be undertaken via software.